Minimum Attention Controller Synthesis for Omega-Regular Objectives

  • Krishnendu Chatterjee
  • Rupak Majumdar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6919)

Abstract

A controller for a discrete game with ω-regular objectives requires attention if, intuitively, it requires measuring the state and switching from the current control action. Minimum attention controllers are preferable in modern shared implementations of cyber-physical systems because they produce the least burden on system resources such as processor time or communication bandwidth. We give algorithms to compute minimum attention controllers for ω-regular objectives in imperfect information discrete two-player games. We show a polynomial-time reduction from minimum attention controller synthesis to synthesis of controllers for mean-payoff parity objectives in games of incomplete information. This gives an optimal EXPTIME-complete synthesis algorithm. We show that the minimum attention controller problem is decidable for infinite state systems with finite bisimulation quotients. In particular, the problem is decidable for timed and rectangular automata.

Keywords

Switching Cost Reward Function Imperfect Information Priority Function Minimum Attention 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Krishnendu Chatterjee
    • 1
  • Rupak Majumdar
    • 2
  1. 1.ISTAustria
  2. 2.MPI-SWSGermany

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